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Approximation by Combinations of ReLU and Squared ReLU Ridge Functions With$ell^1$and$ell^0$Controls

机译:结合使用ReLU和平方ReLU Ridge函数并以 $ ell ^ 1 $ $ ell ^ 0 $ 控件

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We establish L∞and L2error bounds for functions of many variables that are approximated by linear combinations of rectified linear unit (ReLU) and squared ReLU ridge functions with ℓ1and ℓ0controls on their inner and outer parameters. With the squared ReLU ridge function, we show that the L2approximation error is inversely proportional to the inner layer ℓ0sparsity and it need only be sublinear in the outer layer ℓ0sparsity. Our constructions are obtained using a variant of the Maurey-Jones-Barron probabilistic method, which can be interpreted as either stratified sampling with proportionate allocation or two-stage cluster sampling. We also provide companion error lower bounds that reveal near optimality of our constructions. Despite the sparsity assumptions, we showcase the richness and flexibility of these ridge combinations by defining a large family of functions, in terms of certain spectral conditions, that are particularly well approximated by them.
机译:我们建立L n n和L n 2 n的误差范围是由变量线性函数近似的,这些线性变量是由linear n 1 nandℓ n 0 < / sup> n控制它们的内部和外部参数。使用平方的ReLU脊函数,我们显示L n 2 n近似误差与内层成反比ℓ n 0 nsparsity,它只需要在外层sub n 0 nsparsity 。我们的构造是使用Maurey-Jones-Barron概率方法的一种变体获得的,该方法可以解释为按比例分配的分层抽样或两阶段聚类抽样。我们还提供伴随误差下限,以揭示我们的构造的接近最优性。尽管有稀疏性假设,但我们通过在某些频谱条件下定义了一个由它们特别近似的大功能族,展示了这些岭组合的丰富性和灵活性。

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